Fault detection and power quality analysis of wind turbine system using integrated systems

Abstract

Growth in the need for electric energy and fossil fuel scarcity endorses renewable energy generation sources. The generation cost of electric power utilizing wind turbines is cost-effective and straightforward compared to other renewable energy sources (RES). Recently, hasty research and developments have been presented in wind turbines (WT) by researchers globally. Although wind-based energy production is more content, planting the WT is challenging. Maintaining the WT from fault incidence is highly crucial. The fault in the WT distresses the power quality of the produced energy. This condensed power quality affects the transmission systems, substations, and loading end of the renewable source. Also, gear malfunctioning is the primary reason for most of the downtime in wind turbines. This work successfully proposed and implemented a deoxyribonucleic acid (DNA) sequencing-based control technique to reduce the drive train vibration. Therefore, fault detection and monitoring in WTs play an active part in power production and quality maintenance. In this work, a vibration-grounded WT gearbox fault observing scheme is proposed to increase the power quality. Precisely, a wavelet is executed to chart the vibration gesture. Also, the current sensor gesture is implemented to discover the power quality variances associated with the WT's vibration magnitude.